自适应量子拓扑的动态拓扑变换驱动优化

Jincheng Zhang

Published Sep 7, 2026• 0 citations

Abstract

This paper introduces a novel optimization algorithm based on adaptive quantum topology, leveraging the inherent structure of quantum systems to achieve precise parameter control and predictive capabilities. The algorithm utilizes a dynamic topology transformation process, which adjusts the topology of the system to guide the optimization process. This approach offers a fundamentally different methodology compared to traditional optimization techniques, particularly in the context of complex systems governed by quantum properties. We present a comprehensive analysis of the algorithm's design, demonstrating its effectiveness through theoretical analysis and preliminary experimental validation. The core mechanism centers around dynamically modifying the topology to influence the system's evolution, offering a robust framework for optimizing complex systems.

DOI: 10.5281/zenodo.22619401

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